SEYONE CHITHRANANDA

SEYONE CHITHRANANDA

Computer Science student at UC Berkeley (2021)
Machine Learning Intern at Nurix Therapeutics (2021)
Publications in Expert Opinions in Drug Discovery, NeurIPS Machine Learning for Molecules (2020-21)
Research Intern in University of Toronto’s Guzik Lab (2020)
Emergent Ventures Research Scholarship (Mercatus Centre) (2020)
Tensorflow Research Cloud Fellowship (2020)
Re-Work Young Researcher to Watch (2019)

My goal is to develop complex models of disease biology and chemical space using laboratory automation, high-throughput assays, and machine learning. By creating advanced tooling for biology, I hope to solve important problems in biotech, healthcare and hard-tech.

I’m interested in applying computation to drug discovery at the intersection of graph representational learning, natural language processing and molecular property prediction. I’m currently interning on the Machine Learning team at Nurix Therapeutics, a public biotech company in San Francisco aiming to discover immuno-oncology drugs that harness the body’s natural process to control protein levels. I’m also an incoming freshman at UC Berkeley studying computer science and math.

Previously, I worked on researching cutting-edge applications for drug discovery using machine learning, as a research intern at the Matter Lab at the University of Toronto. I was supervised by Prof. Alan Aspuru-Guzik. Alongside my work there, I’m on the open-source developer team for DeepChem, a project aiming to build scientific drug discovery tools using machine learning, based out of Stanford University.